Machine Learning Tools in Natural Language Processing
This tutorial explores the use of SNoW and FEX, two of our core
machine learning tools, to solve text processing problems. Specifically,
we apply FEX and SNoW to context sensitive spelling, named entity tagging,
and document classification.
The tutorial also uses a number of our other standard tools (such as
our Part-of-Speech tagger) and custom scripts to preprocess data for each
task, and touches on ways to streamline the process using perl and shell
scripts, and SNoW and FEX's server modes.
Tutorial Slides
The gzipped .pdf file below contains the slides for this tutorial.
pdf slides
We also have Power Point files for each of the slides, which should contain fewer errors.
Introduction
Machine Learning Abstract
Preprocessing
Fex
Fex extensions
SNoW
NE tagging
Document Classification
Tutorial tarballs
These tarballs contains scripts and data for use in the tutorial.
new fex
new snow
tutorial scripts
server scripts
spell example
new shallow parser
CSCL library
tutorial data
document classifier matls
document classifier processed data
ne tagging postprocess
fex scripts
relabel.awk
FEX examples
SNoW tuning script